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Get Started Free →Guides security professionals in implementing defense-in-depth security architectures, achieving compliance with industry frameworks (SOC2, ISO27001, GDPR, HIPAA), conducting threat modeling and risk assessments, managing security operations and incident response, and embedding security throughout the SDLC.
SkillScore82/100
Test results 82
3/3 safety checks passed
59%82%of test cases passed +23 pts
Passed 18 of 22 test cases with the skill, and 13 of 22 without it.
5 fixed13 passed either way4 still failing0 broke
One test taskSecurity scans flagged a CVE with a CVSS base score of 8.0 on a dedicated non-production development testing server that contains synthetic mock data and no live integrations. Calculate the context-adjusted priority score and specify the patching SLA.
Adds every file the skill has, pinned so you can update it. No account needed.
pip install "decimalai>=0.15"
decimalai skills add davila7-security-compliance
claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"The same install from Python, for a notebook or a setup script.
pip install "decimalai>=0.15"from decimalai import skillpkg
# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("davila7-security-compliance")
if result.exit_code:
raise SystemExit(result.problems)
print("Added. Start Claude Code with the command below.")claude --plugin-dir "$(git rev-parse --show-toplevel 2>/dev/null || pwd)/.agents"Type these in a Claude Code session. No account or API key. It writes the skill and any files it bundles, and asks first when its safety rating isn't Passed.
/plugin marketplace add decimal-labs/decimalai-claude-plugins
/plugin install decimalai@decimalai/decimalai:install davila7-security-complianceThe plugin needs python3 and curl on your machine.
No Python or account. Claude Code picks it up in its next session.
curl -fsSL --create-dirs -o .claude/skills/davila7-security-compliance/SKILL.md https://app.decimal.ai/s/davila7-security-compliance/SKILL.md.claude/skills/davila7-security-compliance/SKILL.mdThis gets SKILL.md only. The skill's 2 other files are not included.
agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[claude-agent-sdk]"
decimalai skills add davila7-security-complianceimport asyncio
from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
async def main():
question = "Hello!"
async with support.run(question) as run: # one user message, one run
async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
print(message)
# In a notebook or async code: await main()
asyncio.run(main())Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.
The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[claude-agent-sdk]"from decimalai import skillpkg
# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("davila7-security-compliance")
if result.exit_code:
raise SystemExit(result.problems)
import asyncio
from claude_agent_sdk import ClaudeAgentOptions
from decimalai.claude_agent_sdk import agent_config
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
async def main():
question = "Hello!"
async with support.run(question) as run: # one user message, one run
async for message in run.query(options=ClaudeAgentOptions(max_turns=6)):
print(message)
# In a notebook or async code: await main()
asyncio.run(main())Prefer its own loader? ClaudeAgentOptions(plugins=[skills_plugin()], skills="all") reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.
No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.
.agents/skills/davila7-security-compliance/SKILL.mdimport asyncio
from pathlib import Path
from claude_agent_sdk import ClaudeAgentOptions, query
skill = Path(".agents/skills/davila7-security-compliance/SKILL.md").read_text()
options = ClaudeAgentOptions(system_prompt=f"You are a helpful agent.\n\n{skill}", max_turns=6)
async def main():
async for message in query(prompt="Hello!", options=options):
print(message)
# In a notebook or async code: await main()
asyncio.run(main())This gets SKILL.md only. The skill's 2 other files are not included.
agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[openai-agents]"
decimalai skills add davila7-security-compliancefrom agents import Agent, Runner
from decimalai.openai_agents import agent_config
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
agent = Agent(
name=support.name,
instructions=support.instructions, # your prompt, then the skill list
tools=[*support.tools], # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.
The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[openai-agents]"from decimalai import skillpkg
# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("davila7-security-compliance")
if result.exit_code:
raise SystemExit(result.problems)
from agents import Agent, Runner
from decimalai.openai_agents import agent_config
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
agent = Agent(
name=support.name,
instructions=support.instructions, # your prompt, then the skill list
tools=[*support.tools], # your tools, then load_skill
)
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")Using SandboxAgent? capabilities=[Shell(), decimalai.openai_agents.sandbox_skills()] points its own loader at the same folder.
No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.
.agents/skills/davila7-security-compliance/SKILL.mdfrom pathlib import Path
from agents import Agent, Runner
skill = Path(".agents/skills/davila7-security-compliance/SKILL.md").read_text()
agent = Agent(name="support", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await Runner.run(agent, "Hello!")
result = Runner.run_sync(agent, "Hello!")This gets SKILL.md only. The skill's 2 other files are not included.
agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[openai]"
decimalai skills add davila7-security-complianceimport json
from openai import OpenAI
from decimalai.openai import agent_config
client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
def lookup_order(order_id: str) -> str:
return f"Order {order_id} shipped yesterday."
# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
"name": "lookup_order",
"description": "Look up the status of an order.",
"parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
"required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}
question = "Where is order A1001?"
with support.run(question) as run: # one user message, one run
# run.system is your prompt, then the skill list.
messages = [{"role": "system", "content": run.system}, run.message]
while True:
reply = client.chat.completions.create(
model="gpt-5.4-mini",
messages=messages,
tools=[*TOOLS, *run.tools], # your tools, then load_skill
).choices[0].message
messages.append(reply)
if not reply.tool_calls:
break
for call in reply.tool_calls:
# load_skill is answered by the run; your own tools by FUNCTIONS.
function = FUNCTIONS.get(call.function.name)
messages.append(run.tool_result(call) or {
"role": "tool", "tool_call_id": call.id,
"content": function(**json.loads(call.function.arguments)) if function
else f"There is no tool named {call.function.name!r}.",
})
print(reply.content)
# The Responses API takes run.response_tools instead of run.tools.The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[openai]"from decimalai import skillpkg
# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("davila7-security-compliance")
if result.exit_code:
raise SystemExit(result.problems)
import json
from openai import OpenAI
from decimalai.openai import agent_config
client = OpenAI()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
def lookup_order(order_id: str) -> str:
return f"Order {order_id} shipped yesterday."
# Your tools, as Chat Completions takes them, and what answers each.
TOOLS = [{"type": "function", "function": {
"name": "lookup_order",
"description": "Look up the status of an order.",
"parameters": {"type": "object", "properties": {"order_id": {"type": "string"}},
"required": ["order_id"]},
}}]
FUNCTIONS = {"lookup_order": lookup_order}
question = "Where is order A1001?"
with support.run(question) as run: # one user message, one run
# run.system is your prompt, then the skill list.
messages = [{"role": "system", "content": run.system}, run.message]
while True:
reply = client.chat.completions.create(
model="gpt-5.4-mini",
messages=messages,
tools=[*TOOLS, *run.tools], # your tools, then load_skill
).choices[0].message
messages.append(reply)
if not reply.tool_calls:
break
for call in reply.tool_calls:
# load_skill is answered by the run; your own tools by FUNCTIONS.
function = FUNCTIONS.get(call.function.name)
messages.append(run.tool_result(call) or {
"role": "tool", "tool_call_id": call.id,
"content": function(**json.loads(call.function.arguments)) if function
else f"There is no tool named {call.function.name!r}.",
})
print(reply.content)
# The Responses API takes run.response_tools instead of run.tools.No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.
.agents/skills/davila7-security-compliance/SKILL.mdfrom pathlib import Path
from openai import OpenAI
client = OpenAI()
skill = Path(".agents/skills/davila7-security-compliance/SKILL.md").read_text()
reply = client.chat.completions.create(
model="gpt-5.4-mini",
messages=[
{"role": "system", "content": f"You are a helpful agent.\n\n{skill}"},
{"role": "user", "content": "Hello!"},
],
).choices[0].messageThis gets SKILL.md only. The skill's 2 other files are not included.
agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[anthropic]"
decimalai skills add davila7-security-complianceimport anthropic
from decimalai.anthropic import agent_config
client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
question = "Hello!"
with support.run(question) as run: # one user message, one run
answer = client.beta.messages.tool_runner(
model="claude-haiku-5-5",
max_tokens=4096,
system=run.system, # your prompt, then the skill list
tools=[*run.tools], # your tools, then load_skill
messages=[{"role": "user", "content": question}],
).until_done()The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[anthropic]"from decimalai import skillpkg
# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("davila7-security-compliance")
if result.exit_code:
raise SystemExit(result.problems)
import anthropic
from decimalai.anthropic import agent_config
client = anthropic.Anthropic()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
question = "Hello!"
with support.run(question) as run: # one user message, one run
answer = client.beta.messages.tool_runner(
model="claude-haiku-5-5",
max_tokens=4096,
system=run.system, # your prompt, then the skill list
tools=[*run.tools], # your tools, then load_skill
messages=[{"role": "user", "content": question}],
).until_done()No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.
.agents/skills/davila7-security-compliance/SKILL.mdfrom pathlib import Path
import anthropic
client = anthropic.Anthropic()
skill = Path(".agents/skills/davila7-security-compliance/SKILL.md").read_text()
reply = client.messages.create(
model="claude-haiku-5-5",
max_tokens=4096,
system=f"You are a helpful agent.\n\n{skill}",
messages=[{"role": "user", "content": "Hello!"}],
)This gets SKILL.md only. The skill's 2 other files are not included.
agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[google-genai]"
decimalai skills add davila7-security-compliancefrom google import genai
from google.genai import types
from decimalai.google_genai import agent_config
client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
def lookup_order(order_id: str) -> str:
return f"Order {order_id} shipped yesterday."
# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
"name": "lookup_order",
"description": "Look up the status of an order.",
"parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
"required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}
question = "Where is order A1001?"
with support.run(question) as run: # one user message, one run
config = types.GenerateContentConfig(
system_instruction=run.system, # your prompt, then the skill list
tools=[*TOOLS, *run.tool_params], # your functions, then load_skill
)
contents = [{"role": "user", "parts": [{"text": run.message}]}]
while True:
response = client.models.generate_content(
model="gemini-3.5-flash", contents=contents, config=config,
)
if not response.function_calls:
break
contents.append(response.candidates[0].content)
parts = []
for call in response.function_calls:
# load_skill is answered by the run; your own functions by FUNCTIONS.
# A loop of your own rather than automatic function calling, which
# raises KeyError when the model asks for a function you did not pass.
function = FUNCTIONS.get(call.name)
parts.append(run.tool_result(call) or {"function_response": {
"name": call.name, "id": call.id,
"response": {"result": function(**(call.args or {})) if function
else f"There is no function named {call.name!r}."},
}})
contents.append({"role": "user", "parts": parts})
print(response.text)The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[google-genai]"from decimalai import skillpkg
# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("davila7-security-compliance")
if result.exit_code:
raise SystemExit(result.problems)
from google import genai
from google.genai import types
from decimalai.google_genai import agent_config
client = genai.Client()
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
def lookup_order(order_id: str) -> str:
return f"Order {order_id} shipped yesterday."
# Your functions, as declarations for the model, and what answers each.
TOOLS = [{"function_declarations": [{
"name": "lookup_order",
"description": "Look up the status of an order.",
"parameters_json_schema": {"type": "object", "properties": {"order_id": {"type": "string"}},
"required": ["order_id"]},
}]}]
FUNCTIONS = {"lookup_order": lookup_order}
question = "Where is order A1001?"
with support.run(question) as run: # one user message, one run
config = types.GenerateContentConfig(
system_instruction=run.system, # your prompt, then the skill list
tools=[*TOOLS, *run.tool_params], # your functions, then load_skill
)
contents = [{"role": "user", "parts": [{"text": run.message}]}]
while True:
response = client.models.generate_content(
model="gemini-3.5-flash", contents=contents, config=config,
)
if not response.function_calls:
break
contents.append(response.candidates[0].content)
parts = []
for call in response.function_calls:
# load_skill is answered by the run; your own functions by FUNCTIONS.
# A loop of your own rather than automatic function calling, which
# raises KeyError when the model asks for a function you did not pass.
function = FUNCTIONS.get(call.name)
parts.append(run.tool_result(call) or {"function_response": {
"name": call.name, "id": call.id,
"response": {"result": function(**(call.args or {})) if function
else f"There is no function named {call.name!r}."},
}})
contents.append({"role": "user", "parts": parts})
print(response.text)No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.
.agents/skills/davila7-security-compliance/SKILL.mdfrom pathlib import Path
from google import genai
from google.genai import types
client = genai.Client()
skill = Path(".agents/skills/davila7-security-compliance/SKILL.md").read_text()
response = client.models.generate_content(
model="gemini-3.5-flash",
contents="Hello!",
config=types.GenerateContentConfig(system_instruction=f"You are a helpful agent.\n\n{skill}"),
)This gets SKILL.md only. The skill's 2 other files are not included.
agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[langchain]" langchain-openai
decimalai skills add davila7-security-compliancefrom langchain.agents import create_agent
from decimalai.langchain import agent_config
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
agent = create_agent(
"openai:gpt-5.4-mini",
tools=[], # your tools; the middleware adds load_skill
middleware=[support.middleware], # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[langchain]" langchain-openaifrom decimalai import skillpkg
# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("davila7-security-compliance")
if result.exit_code:
raise SystemExit(result.problems)
from langchain.agents import create_agent
from decimalai.langchain import agent_config
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
agent = create_agent(
"openai:gpt-5.4-mini",
tools=[], # your tools; the middleware adds load_skill
middleware=[support.middleware], # your prompt, the skill list and load_skill
)
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.
.agents/skills/davila7-security-compliance/SKILL.mdfrom pathlib import Path
from langchain.agents import create_agent
skill = Path(".agents/skills/davila7-security-compliance/SKILL.md").read_text()
agent = create_agent("openai:gpt-5.4-mini", tools=[], system_prompt=f"You are a helpful agent.\n\n{skill}")
result = agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})This gets SKILL.md only. The skill's 2 other files are not included.
CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.
pip install "decimalai>=0.16" "crewai>=1.15.27"
decimalai skills add davila7-security-complianceimport decimalai.crewai
from crewai import Agent, Crew, Task
agent = Agent(
role="Support", goal="Help the customer", backstory="A support agent.",
llm=llm, # your own CrewAI LLM
skills=decimalai.crewai.skills(), # the installed folder
tools=decimalai.crewai.skill_tools(), # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()The same install from Python, for a notebook or a setup script. CrewAI's own skill loader reads the installed folder. No DecimalAI account needed.
pip install "decimalai>=0.16" "crewai>=1.15.27"from decimalai import skillpkg
# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("davila7-security-compliance")
if result.exit_code:
raise SystemExit(result.problems)
import decimalai.crewai
from crewai import Agent, Crew, Task
agent = Agent(
role="Support", goal="Help the customer", backstory="A support agent.",
llm=llm, # your own CrewAI LLM
skills=decimalai.crewai.skills(), # the installed folder
tools=decimalai.crewai.skill_tools(), # reads a skill's files, runs its scripts
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()No DecimalAI package. CrewAI's own loader reads the folder, and nothing pins or updates it.
.agents/skills/davila7-security-compliance/SKILL.mdfrom pathlib import Path
from crewai import Agent, Crew, Task
agent = Agent(
role="Support", goal="Help the customer", backstory="A support agent.",
llm=llm, # your own CrewAI LLM
skills=[Path(".agents/skills")],
)
task = Task(description="Hello!", expected_output="an answer", agent=agent)
Crew(agents=[agent], tasks=[task]).kickoff()This gets SKILL.md only. The skill's 2 other files are not included.
agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[adk]"
decimalai skills add davila7-security-compliancefrom decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
agent = LlmAgent(
name="support", # ADK needs a Python identifier
model="gemini-3.5-flash",
instruction=support.instruction, # your prompt, then the skill list
tools=[*support.tools], # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.
The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[adk]"from decimalai import skillpkg
# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("davila7-security-compliance")
if result.exit_code:
raise SystemExit(result.problems)
from decimalai.adk import DecimalAIPlugin, agent_config
from google.adk.agents import LlmAgent
from google.adk.apps import App
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
agent = LlmAgent(
name="support", # ADK needs a Python identifier
model="gemini-3.5-flash",
instruction=support.instruction, # your prompt, then the skill list
tools=[*support.tools], # your tools, then load_skill
)
# DecimalAIPlugin makes each invocation of runners built from this App one trace.
app = App(name="support", root_agent=agent, plugins=[DecimalAIPlugin()])Prefer ADK's own loader? SkillToolset(skills=decimalai.adk.skills(), ...) reads the same folder. Use one or the other: a skill delivered both ways reaches the prompt twice.
No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.
.agents/skills/davila7-security-compliance/SKILL.mdfrom pathlib import Path
from google.adk.agents import LlmAgent
skill = Path(".agents/skills/davila7-security-compliance/SKILL.md").read_text()
agent = LlmAgent(
name="support",
model="gemini-3.5-flash",
instruction=lambda context: f"You are a helpful agent.\n\n{skill}",
)This gets SKILL.md only. The skill's 2 other files are not included.
agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[pydantic-ai]"
decimalai skills add davila7-security-compliancefrom pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
agent = Agent(
"openai:gpt-4o-mini",
name=support.name,
tools=[], # your tools; the capability adds load_skill
capabilities=[support], # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.
The same install from Python, for a notebook or a setup script. agent_config() hands your agent the skill. With no DecimalAI key it reads your project's files and sends nothing. Needs SDK 0.27 or newer.
pip install "decimalai[pydantic-ai]"from decimalai import skillpkg
# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("davila7-security-compliance")
if result.exit_code:
raise SystemExit(result.problems)
from pydantic_ai import Agent
from decimalai.pydantic_ai import agent_config
# With no DECIMAL_API_KEY this reads the skills your project lists, from disk.
support = agent_config("support", fallback="You are a helpful agent.")
agent = Agent(
"openai:gpt-4o-mini",
name=support.name,
tools=[], # your tools; the capability adds load_skill
capabilities=[support], # your prompt, the skill list and load_skill
)
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")On the Pydantic AI harness, decimalai.pydantic_ai_harness.skills(project) uses its own loader instead.
No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.
.agents/skills/davila7-security-compliance/SKILL.mdfrom pathlib import Path
from pydantic_ai import Agent
skill = Path(".agents/skills/davila7-security-compliance/SKILL.md").read_text()
agent = Agent("openai:gpt-4o-mini", instructions=f"You are a helpful agent.\n\n{skill}")
# In a notebook or async code: result = await agent.run("Hello!")
result = agent.run_sync("Hello!")This gets SKILL.md only. The skill's 2 other files are not included.
Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.
pip install "decimalai>=0.16" deepagents
decimalai skills add davila7-security-complianceimport decimalai.deepagents
from deepagents import create_deep_agent
agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).
The same install from Python, for a notebook or a setup script. Deep Agents' own skill loader reads the installed folder. No DecimalAI account needed.
pip install "decimalai>=0.16" deepagentsfrom decimalai import skillpkg
# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("davila7-security-compliance")
if result.exit_code:
raise SystemExit(result.problems)
import decimalai.deepagents
from deepagents import create_deep_agent
agent = create_deep_agent(model=model, **decimalai.deepagents.skills())
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})The default backend reads files but has no shell. To run a skill's scripts, pass skills(backend=LocalShellBackend(...)).
No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.
.agents/skills/davila7-security-compliance/SKILL.mdfrom pathlib import Path
from deepagents import create_deep_agent
skill = Path(".agents/skills/davila7-security-compliance/SKILL.md").read_text()
agent = create_deep_agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent.invoke({"messages": [{"role": "user", "content": "Hello!"}]})This gets SKILL.md only. The skill's 2 other files are not included.
Its own skill loader reads the installed folder. No DecimalAI account needed.
pip install "decimalai>=0.16" agent-framework
decimalai skills add davila7-security-complianceimport asyncio
from agent_framework import Agent
from decimalai.agent_framework import skills
agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))It caches skills by default, so restart the process after decimalai skills update.
The same install from Python, for a notebook or a setup script. Its own skill loader reads the installed folder. No DecimalAI account needed.
pip install "decimalai>=0.16" agent-frameworkfrom decimalai import skillpkg
# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("davila7-security-compliance")
if result.exit_code:
raise SystemExit(result.problems)
import asyncio
from agent_framework import Agent
from decimalai.agent_framework import skills
agent = Agent(client=client, instructions="You are a helpful agent.", context_providers=[skills()])
asyncio.run(agent.run("Hello!"))It caches skills by default, so restart the process after decimalai skills update.
No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.
.agents/skills/davila7-security-compliance/SKILL.mdimport asyncio
from pathlib import Path
from agent_framework import Agent
skill = Path(".agents/skills/davila7-security-compliance/SKILL.md").read_text()
agent = Agent(client=client, instructions=f"You are a helpful agent.\n\n{skill}")
asyncio.run(agent.run("Hello!"))This gets SKILL.md only. The skill's 2 other files are not included.
Strands' own skill loader reads the installed folder. No DecimalAI account needed.
pip install "decimalai>=0.16" strands-agents
decimalai skills add davila7-security-compliancefrom decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell
agent = Agent(
model=model, # always pass one: the default is Amazon Bedrock
system_prompt="You are a helpful agent.",
tools=[file_editor, shell],
plugins=[skills()],
)
agent("Hello!")Strands loads an agent's skills once, so build the agent again after decimalai skills update.
The same install from Python, for a notebook or a setup script. Strands' own skill loader reads the installed folder. No DecimalAI account needed.
pip install "decimalai>=0.16" strands-agentsfrom decimalai import skillpkg
# Writes .agents/skills and .decimal/skills.toml. Safe to run twice.
result = skillpkg.add("davila7-security-compliance")
if result.exit_code:
raise SystemExit(result.problems)
from decimalai.strands import skills
from strands import Agent
from strands.vended_tools import file_editor, shell
agent = Agent(
model=model, # always pass one: the default is Amazon Bedrock
system_prompt="You are a helpful agent.",
tools=[file_editor, shell],
plugins=[skills()],
)
agent("Hello!")Strands loads an agent's skills once, so build the agent again after decimalai skills update.
No DecimalAI package. The whole skill goes in every prompt, and nothing pins or updates it.
.agents/skills/davila7-security-compliance/SKILL.mdfrom pathlib import Path
from strands import Agent
skill = Path(".agents/skills/davila7-security-compliance/SKILL.md").read_text()
agent = Agent(model=model, system_prompt=f"You are a helpful agent.\n\n{skill}")
agent("Hello!")This gets SKILL.md only. The skill's 2 other files are not included.
Adds every file the skill has, pinned so you can update it. Cursor, Copilot, Cline and Warp read this folder by themselves.
pip install "decimalai>=0.15"
decimalai skills add davila7-security-complianceNo Python or account. Cursor, Copilot, Cline and Warp read this folder by themselves.
curl -fsSL --create-dirs -o .agents/skills/davila7-security-compliance/SKILL.md https://app.decimal.ai/s/davila7-security-compliance/SKILL.md.agents/skills/davila7-security-compliance/SKILL.mdThis gets SKILL.md only. The skill's 2 other files are not included.
Give its text to your model as instructions. No account or package needed.
This gets SKILL.md only. The skill's 2 other files are not included.
Raw files: /s/davila7-security-compliance/SKILL.md · /s/davila7-security-compliance.json
Fetch the file and give its text to your model as instructions. No account or package needed.
curl -fsSL https://app.decimal.ai/s/davila7-security-compliance/SKILL.mdcurl -fsSL https://app.decimal.ai/s/davila7-security-compliance.jsonThis gets SKILL.md only. The skill's 2 other files are not included.
You don't need a DecimalAI account.
Saved prompts and skills, pinned versions, and traces of this skill in your runs. DecimalAI does not run your agent.
Claude Code reads files from your project, so DecimalAI config does not apply there.
On Claude Agent SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.
On OpenAI Agents: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.
On OpenAI SDK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.
On Anthropic: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.
On Gemini API: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.
On LangChain: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.
On CrewAI: set DECIMAL_API_KEY and add decimalai.init(crewai=True) to record runs and skill use. The skill version stays in your repo.
On Google ADK: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.
On Pydantic AI: save the skill to an agent here, set DECIMAL_API_KEY, and the same code uses it with no command to run. Changes you save reach the next run with no redeploy.
On Deep Agents: set DECIMAL_API_KEY and add decimalai.init(langchain=True) to record runs and skill use. The skill version stays in your repo.
On Microsoft Agent Framework: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.
On Strands: set DECIMAL_API_KEY and add decimalai.init(otel=True, agent_name="support") to record runs and skill use. The skill version stays in your repo.
Editors read files from your project, so DecimalAI config does not apply there.
Anywhere else: record a use with decimalai.log_skill_activation() inside a trace.
Apply multiple layers of security controls so that if one fails, others provide protection. Never rely on a single security mechanism.
Never trust, always verify. Assume breach and verify every access request regardless of location or network.
Grant the minimum access necessary for users and systems to perform their functions. Regularly review and revoke unused permissions.
Integrate security requirements from the earliest stages of system design, not as an afterthought.
Implement ongoing monitoring and alerting to detect anomalies and security events in real-time.
Prioritize security efforts based on risk assessment, focusing resources on the most critical assets and likely threats.
Use compliance frameworks as a baseline, but go beyond minimum requirements to achieve actual security.
Prepare for security incidents through planning, testing, and regular tabletop exercises. Assume compromise will occur.
Objective: Understand current security posture and compliance requirements
Activities:
Deliverables:
Objective: Design secure systems and architectures
Activities:
Deliverables:
Objective: Deploy security controls and harden systems
Activities:
Deliverables:
Objective: Continuously monitor for threats and anomalies
Activities:
Deliverables:
Objective: Respond to security incidents and recover operations
Activities:
Deliverables:
Objective: Validate compliance and continuously improve security
Activities:
Deliverables:
When to use: Evaluating security risks and prioritizing mitigation efforts
Process:
1. Identify Assets
- What systems, data, and services need protection?
- What is the business value of each asset?
- Who are the asset owners?
2. Identify Threats
- What threat actors might target these assets? (nation-state, cybercriminals, insiders)
- What are their motivations? (financial gain, espionage, disruption)
- What are current threat trends?
3. Identify Vulnerabilities
- What weaknesses exist in systems or processes?
- What security controls are missing or ineffective?
- What are known CVEs affecting your systems?
4. Calculate Risk
Risk = Likelihood × Impact
Likelihood scale (1-5):
1 = Rare (< 5% chance in 1 year)
2 = Unlikely (5-25%)
3 = Possible (25-50%)
4 = Likely (50-75%)
5 = Almost Certain (> 75%)
Impact scale (1-5):
1 = Minimal (< $10K loss, no data breach)
2 = Minor ($10K-$100K, limited data exposure)
3 = Moderate ($100K-$1M, significant data breach)
4 = Major ($1M-$10M, extensive data breach, regulatory fines)
5 = Catastrophic (> $10M, business-threatening)
Risk Score = Likelihood × Impact (max 25)
5. Prioritize Risks
- Critical: Risk score 15-25 (immediate action)
- High: Risk score 10-14 (action within 30 days)
- Medium: Risk score 5-9 (action within 90 days)
- Low: Risk score 1-4 (monitor and accept)
6. Determine Risk Response
- Mitigate: Implement controls to reduce risk
- Accept: Document acceptance if risk is within tolerance
- Transfer: Use insurance or third-party services
- Avoid: Eliminate the activity that creates risk
Output: Risk register with prioritized risks and mitigation plans
When to use: Choosing appropriate security controls for identified risks
Framework: Use NIST CSF categories or CIS Controls
NIST CSF Functions:
1. Identify (ID)
- Asset Management
- Risk Assessment
- Governance
2. Protect (PR)
- Access Control
- Data Security
- Protective Technology
3. Detect (DE)
- Anomalies and Events
- Security Monitoring
- Detection Processes
4. Respond (RS)
- Response Planning
- Communications
- Analysis and Mitigation
5. Recover (RC)
- Recovery Planning
- Improvements
- Communications
Control Types:
- Preventive: Stop incidents before they occur (MFA, firewalls, encryption)
- Detective: Identify incidents when they occur (SIEM, IDS, log monitoring)
- Corrective: Fix issues after detection (patching, incident response)
- Deterrent: Discourage attackers (security policies, warnings)
- Compensating: Alternative controls when primary controls aren't feasible
Selection Criteria:
1. Does it address the identified risk?
2. Is it cost-effective? (Control cost < Risk value)
3. Is it technically feasible?
4. Does it meet compliance requirements?
5. Can we maintain and monitor it?
When to use: Determining which compliance frameworks to implement
Decision Tree:
What type of organization are you?
├─ SaaS/Cloud Service Provider
│ ├─ Selling to enterprises? → SOC2 Type II (required)
│ ├─ International customers? → ISO27001 (strongly recommended)
│ ├─ Handling health data? → HIPAA + HITRUST
│ └─ Handling payment cards? → PCI-DSS
├─ Healthcare Provider/Payer
│ ├─ U.S.-based → HIPAA (required)
│ ├─ International → HIPAA + GDPR
│ └─ Plus: HITRUST for comprehensive framework
├─ Financial Services
│ ├─ U.S. banks → GLBA, SOX (if public)
│ ├─ Payment processing → PCI-DSS (required)
│ ├─ International → ISO27001, local regulations
│ └─ Plus: NIST CSF for framework
├─ E-commerce/Retail
│ ├─ Accept credit cards → PCI-DSS (required)
│ ├─ EU customers → GDPR (required)
│ ├─ California customers → CCPA
│ └─ B2B sales → SOC2 Type II
└─ General Enterprise
├─ Selling to enterprises → SOC2 Type II
├─ Want broad recognition → ISO27001
├─ Government contracts → FedRAMP, NIST 800-53
└─ Industry-specific → Check sector regulations
Multi-Framework Strategy:
- Start with: SOC2 or ISO27001 (choose one as foundation)
- Add: Data privacy regulations (GDPR, CCPA) as needed
- Layer on: Industry-specific requirements
When to use: Triaging and responding to security incidents
Severity Levels:
P0 - Critical (Immediate Response)
- Active breach with data exfiltration occurring
- Ransomware encryption in progress
- Complete system outage of critical services
- Unauthorized access to production databases
- Response: Engage CIRT immediately, executive notification, 24/7 effort
P1 - High (Response within 1 hour)
- Confirmed malware on critical systems
- Attempted unauthorized access to sensitive data
- DDoS attack affecting availability
- Significant vulnerability with active exploits
- Response: Engage CIRT, manager notification, work until contained
P2 - Medium (Response within 4 hours)
- Malware on non-critical systems
- Suspicious account activity
- Policy violations with security impact
- Vulnerability requiring patching
- Response: Security team investigation, business hours
P3 - Low (Response within 24 hours)
- Failed login attempts (below threshold)
- Minor policy violations
- Informational security events
- Response: Standard queue, document findings
Classification Factors:
1. Data confidentiality impact (PHI, PII, financial, IP)
2. System availability impact (revenue, operations)
3. Data integrity impact (corruption, unauthorized changes)
4. Number of affected systems/users
5. Regulatory reporting requirements
When to use: Prioritizing vulnerability remediation
Framework: Enhanced CVSS with business context
Base CVSS Score × Business Context Multiplier = Priority Score
CVSS Severity Ranges:
- Critical: 9.0-10.0
- High: 7.0-8.9
- Medium: 4.0-6.9
- Low: 0.1-3.9
Business Context Multipliers:
- Internet-facing production system: 2.0×
- Internal production system: 1.5×
- Systems with sensitive data: 1.5×
- Development/test environment: 0.5×
- Active exploit in the wild: 2.0×
- Compensating controls in place: 0.7×
Priority Levels:
- P0 (Critical): Score ≥ 14 → Patch within 24-48 hours
- P1 (High): Score 10-13.9 → Patch within 7 days
- P2 (Medium): Score 6-9.9 → Patch within 30 days
- P3 (Low): Score < 6 → Patch within 90 days or accept risk
Additional Considerations:
- Can the system be isolated/segmented?
- Are there effective detective controls?
- What is the patching complexity/risk?
- Is there a vendor patch available?
When to use: Evaluating security risks of vendors and partners
Assessment Framework:
1. Categorize Vendor Risk Level
Low Risk (Minimal assessment):
- No access to systems or data
- Limited integration
- Non-critical service
→ Simple questionnaire
Medium Risk (Standard assessment):
- Limited system access
- Non-sensitive data access
- Important but not critical service
→ Security questionnaire + evidence review
High Risk (Comprehensive assessment):
- Production system access
- Sensitive data processing
- Critical service dependency
→ Full assessment + audit reports + pen test
Critical Risk (Extensive assessment):
- Full production access
- PHI/PII processing
- Business-critical dependency
→ On-site audit + continuous monitoring + SLA
2. Assessment Components
For Medium/High/Critical vendors:
□ Security questionnaire (SIG, CAIQ, or custom)
□ Compliance certifications (SOC2, ISO27001)
□ Insurance certificates (cyber liability)
□ Security policies and procedures
□ Incident response plan
□ Disaster recovery/business continuity plan
□ Data processing agreement (DPA)
□ Penetration test results (for high/critical)
□ Right to audit clause in contract
3. Ongoing Monitoring
- Annual reassessment
- Monitor for breaches/incidents
- Review security updates and patches
- Track compliance certification renewals
- Conduct periodic audits (for critical vendors)
4. Vendor Risk Score
Calculate score (0-100):
- Security maturity: 40 points
- Compliance certifications: 20 points
- Incident history: 15 points
- Financial stability: 15 points
- References and reputation: 10 points
Action based on score:
- 80-100: Approved
- 60-79: Approved with conditions
- 40-59: Requires remediation plan
- < 40: Do not engage
1. Detection & Alert
↓
2. Triage & Classification
- Determine severity (P0-P3)
- Assign to responder
↓
3. Investigation
- Gather evidence
- Analyze logs (SIEM)
- Determine scope
↓
4. Containment
- Isolate affected systems
- Block malicious IPs/domains
- Disable compromised accounts
↓
5. Eradication
- Remove malware
- Close vulnerabilities
- Patch systems
↓
6. Recovery
- Restore from backups
- Verify system integrity
- Return to production
↓
7. Post-Incident Review
- Document timeline
- Root cause analysis
- Update playbooks
- Implement improvements
↓
8. Reporting
- Executive summary
- Regulatory notification (if required)
- Stakeholder communication
1. Asset Discovery
- Scan network for assets
- Maintain asset inventory
↓
2. Vulnerability Scanning
- Authenticated scans
- Unauthenticated scans
- Agent-based monitoring
↓
3. Assessment & Validation
- Validate findings
- Remove false positives
- Add business context
↓
4. Prioritization
- Apply CVSS + context
- Assign severity (P0-P3)
- Create remediation tickets
↓
5. Remediation
- Patch systems
- Apply compensating controls
- Update configurations
↓
6. Verification
- Rescan to confirm fix
- Update vulnerability status
↓
7. Reporting
- Metrics dashboard
- Executive reports
- Trend analysis
1. Schedule Review (Quarterly)
↓
2. Generate Access Reports
- User access by role
- Privileged accounts
- Service accounts
- Orphaned accounts
↓
3. Distribute to Managers
- Each manager reviews their team
- Certify appropriate access
↓
4. Review & Certify
- Approve legitimate access
- Flag inappropriate access
- Identify orphaned accounts
↓
5. Remediation
- Revoke unapproved access
- Disable orphaned accounts
- Update RBAC assignments
↓
6. Document & Report
- Certification completion rate
- Access changes made
- Compliance evidence
1. Scoping (3-4 months before)
- Define in-scope systems
- Select Trust Service Criteria
- Engage auditor
↓
2. Gap Assessment (2-3 months before)
- Map controls to requirements
- Identify control gaps
- Create remediation plan
↓
3. Readiness (1-2 months before)
- Implement missing controls
- Document policies/procedures
- Conduct mock audit
↓
4. Evidence Collection (Ongoing)
- Automate evidence gathering
- Organize evidence repository
- Prepare control narratives
↓
5. Audit Kickoff
- Provide evidence to auditor
- Respond to requests
- Schedule interviews
↓
6. Fieldwork (4-6 weeks)
- Auditor tests controls
- Provide additional evidence
- Address findings
↓
7. Report Issuance
- Review draft report
- Address any exceptions
- Receive final SOC2 report
↓
8. Continuous Monitoring
- Monitor control effectiveness
- Prepare for next audit cycle
Skills that do similar work, with their headline benchmark lift.
From the same source and nearby in the catalogue.